Abstract: Systems and methods for implementing machine-learning models for ovarian stimulation is described herein. In some variations, a computer-implemented method may include optimizing an ovarian stimulation process may include receiving patient-specific data associated with a patient, and predicting an egg outcome for the patient for each of a plurality of treatment options for an ovarian stimulation process based on at least one predictive model and the patient-specific data, where the at least one predictive model is trained using prior patient-specific data associated with a plurality of prior patients.
Type:
Grant
Filed:
March 29, 2022
Date of Patent:
August 22, 2023
Assignee:
Alife Health Inc.
Inventors:
Kevin Loewke, Paxton Maeder-York, Melissa Teran, Mark Lown, Arielle Sarah Rothman, Veronica Isabella Nutting, Michael Fanton, Jordan Tang